Model-based data structure repair is a promising techniquefor enabling programs to continue to execute successfullyin the face of otherwise fatal data structure corruption errors.Previous research in this eld relied on ...

This thesis seeks to contribute to the understanding of markets populated by boundedly rational agents who learn from experience. Bounded rationality and learning have both been the focus of much research in computer ...

Over the past several decades, technologies for remote sensing and exploration have be- come increasingly powerful but continue to face limitations in the areas of information gathering and analysis. These limitations ...

In much of the theoretical literature on global broadcast algorithms for wireless networks, issues of message dissemination are considered together with issues of contention management. This combination leads to complicated ...

We propose decoupled sampling, an approach that decouples shading from visibility sampling in order to enable motion blur and depth-of-field at reduced cost. More generally, it enables extensions of modern real-time graphics ...

A major obstacle in photography is the presence of distracting elements that pull attention away from the main subject and clutter the composition. In this article, we present a new image-processing technique that reduces ...

In this paper, we prove a conjecture published in 1989 and also partially address an open problem announced at the Conference on Learning Theory (COLT) 2015. For an expected loss function of a deep nonlinear neural network, ...

The IOA language provides notations for defining both primitive and composite I/O automata.This note describes, both formally and with examples, the constraints on these definitions, thecomposability requirements for the ...

In this paper, we introduce the concept of a deionizer. A deionizeris a special type of partial evaluator whose purpose is to create a newversion of a program that can run without accessing a partial set of I/O resources.Although ...

Simple Temporal Networks with Uncertainty provide a useful framework for modeling temporal constraints and, importantly, for modeling actions with uncertain durations. To determine whether we can construct a schedule for ...

This paper presents Delphi, a mobile software controller that helps applications select the best network among available choices for their data transfers. Delphi optimizes a specified objective such as transfer completion ...

This paper describes the design, implementation, and evaluation of Amoeba, a context-sensitive context detection service for mobile devices. Amoeba exports an API that allows a client to express interest in one or more ...

This thesis describes the design, implementation, and evaluation of a replication scheme to handle Byzantine faults in transaction processing database systems. The scheme compares answers from queries and updates on multiple ...

We propose a framework for detecting and tracking multiple interacting objects from a single, static, uncalibrated camera. The number of objects is variable and unknown, and object-class-specific models are not available. ...

The modern intensive care unit (ICU) has become a complex, expensive, data-intensive environment. Caregivers maintain an overall assessment of their patients based on important observations and trends. If an advanced ...

In this thesis I will be concerned with linking the observed speechsignal to the configuration of articulators.Due to the potentially rapid motion of the articulators, the speechsignal can be highly non-stationary. The ...

We can evaluate models of natural intelligence, as well as theirindividual components, by using a model of hardware and developmentcosts, ignoring almost all the details of biology. The basic argumentis that neither the ...

The capability of estimating the walking direction of people would be useful in many applications such as those involving autonomous cars and robots.We introduce an approach for estimating the walking direction of people ...

We present a framework for learning abstract relational knowledge with the aimof explaining how people acquire intuitive theories of physical, biological, orsocial systems. Our approach is based on a generative relational ...

Given a set of images containing multiple object categories,we seek to discover those categories and their image locations withoutsupervision. We achieve this using generative modelsfrom the statistical text literature: ...